We often find it hard to remember the world we left behind, but cast your mind back, say, 20 years, and we lived in a very different world. Personal Computers and the internet were on the rise, and businesses were all becoming connected. This provided companies with immense opportunities in terms of collaboration and digital adoption, and on the flip side, it eased the distribution of computer viruses.
Today we barely even think about our antivirus software and policies. Pretty much every business deploys antivirus agents to their entire network. As it is often said, it's just there.
But what is the antivirus software doing? Well, to put it simply, it runs in the background, ensuring the ins and outs of your devices and network is safe, only highlighting alerts if something goes wrong.
Alongside antivirus software organizations are now deploying application observability software, which monitors and maintains application health in real-time. For example, Datadog Splunk or Dynatrace, to name just a few. This area of monitoring, alerting and remediation has reached a significant level of maturity over the last few years.
So the question is “what does this have to do with data observability?”
Well, a data observability solution can be seen as anti-virus for data issues. By deploying such a solution at source across your data stack, you create a robust data environment, with the ability to detect and alert on data incidents in real-time or near real-time. Not only does data observability at source provide detection and alerts, but it also can provide automated recommendations for remediation.
Deploying data observability is not a complex process. Very much like your antivirus tools, once it is deployed, it can run in the background.
And deploying Kensu it's very straightforward. There is one Kensu platform available either in the public cloud (AWS, Azure, and GCP are all supported) or if needed, the same platform can be deployed within your local data center.
Kensu requires just two lines of code, and you can be up and running in as little as three hours. Finally, typically we see our customers take no more than four weeks to scale up and begin to benefit from data observability. Our customers tell us Kensu applies to the 1/10/100 rule: it is better to spend $1 preventing an issue than $10 to fix an error after the fact, or the $100 cost of failure to fix.
What does the future hold for data observability? As data observability matures in organizations, the real power is harnessed.
At Kensu, we are investing large amounts of research and development effort to increase our platform's intelligence. Our vision for the future of data observability is having data observability at the heart of everything an organization does, so they are protected against data incidents as they are against viruses.